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  1. 1
    An energy efficient reinforcement learning based cooperative channel sensing for cognitive radio sensor networks

    An energy efficient reinforcement learning based cooperative channel sensing for cognitive radio sensor networks by Mustapha, Ibrahim, Mohd Ali, Borhanuddin, Sali, Aduwati, A. Rasid, Mohd Fadlee, Mohamad, Hafizal

    Published 2017
    “…Simulation results show convergence and adaptability of the algorithm to dynamic environment in achieving optimal solutions. …”
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  2. 2
    A reinforcement learning-based energy-efficient spectrum-aware clustering algorithm for cognitive radio wireless sensor network

    A reinforcement learning-based energy-efficient spectrum-aware clustering algorithm for cognitive radio wireless sensor network by Mustapha, Ibrahim

    Published 2016
    “…Simulation results show convergence, learning and adaptability of the RL based algorithms to dynamic environment toward achieving the optimal solutions. …”
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  3. 3
    Assessment of cognitive load using multimedia learning and resting states with deep learning perspective

    Assessment of cognitive load using multimedia learning and resting states with deep learning perspective by Qayyum, A., Faye, I., Malik, A.S., Mazher, M.

    Published 2019
    “…The results shows that alpha brain wave produced consistent behavior using for all cognition tasks based on pre-trained CNN models for classification and cognitive load assessment. …”
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  4. 4
    Development of self-learning algorithm for autonomous system utilizing reinforcement learning and unsupervised weightless neural network / Yusman Yusof

    Development of self-learning algorithm for autonomous system utilizing reinforcement learning and unsupervised weightless neural network / Yusman Yusof by Yusof, Yusman

    Published 2019
    “…In the simulation the robot is equipped with thirteen distance sensing sensors. From the simulation result, by using these sensors information the AUTOWiSARD algorithm can successfully differentiate and classify states without supervision, while the Q-learning algorithm is able to produce and optimized states-actions policy. …”
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  5. 5
    An application of a novel technique for assessing the operating performance of existing cooling systems on a university campus

    An application of a novel technique for assessing the operating performance of existing cooling systems on a university campus by Abdalla, E.A.H., Nallagownden, P., Nor, N.B.M., Romlie, M.F., Hassan, S.M.

    Published 2018
    “…Two contributions in this work are: (1) the prediction of a model by using Adaptive Neuro-Fuzzy Inference System (ANFIS)-based Fuzzy Clustering Subtractive (FCS), and (2) the classification and optimization of the predicted models by using an Accelerated Particle Swarm Optimization (APSO) algorithm. …”
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  6. 6
    Development of Phasor Measurement Unit Based Fault Detection and Faulty Line Classification in Electrical Power System

    Development of Phasor Measurement Unit Based Fault Detection and Faulty Line Classification in Electrical Power System by Muhammad Qasim, Khan

    Published 2019
    “…This model implements Non-Recursive Phasor Estimation (NRPE) algorithm. …”
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  7. 7
    Vector evaluated particle swarm optimization approach to solve assembly sequence planning problem

    Vector evaluated particle swarm optimization approach to solve assembly sequence planning problem by A. Mukred, Jameel A., A. Rahim, Ruzairi, Mohamad, Elmy Johana, Salh, Adeeb, Ashyap, Adel Y. I., Abdullah, Qazwan, AL-Fadhali, Najib, Al-Ameri, S., Al-Ashwal, Rania

    Published 2022
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  8. 8
    Supervised deep learning algorithms for process fault detection and diagnosis under different temporal subsequence length of process data

    Supervised deep learning algorithms for process fault detection and diagnosis under different temporal subsequence length of process data by Terence Chia Yi Kai, Agus Saptoro, Zulfan Adi Putra, King Hann Lim, Wan Sieng Yeo, Jaka Sunarso

    Published 2025
    “…Current FDD technologies mostly rely on data-driven solutions by making full use of abundant process data collected by the state-of-the-art distributed process instruments and sensors. Deep learning algorithms were widely used among all the data-driven algorithms. …”
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  9. 9
    Simulated Kalman Filter with modified measurement, substitution mutation and hamming distance calculation for solving traveling salesman problem

    Simulated Kalman Filter with modified measurement, substitution mutation and hamming distance calculation for solving traveling salesman problem by Suhazri Amrin, Rahmad, Zuwairie, Ibrahim, Zulkifli, Md. Yusof

    Published 2022
    “…There were also attempts to hybridize SKF with other famous algorithms such as Particle Swarm Optimization (PSO), Gravitational Search Algorithm (GSA), and Sine Cosine Algorithm (SCA) to improve its performance. …”
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  10. 10
    Cyberbullying detection: a machine learning approach

    Cyberbullying detection: a machine learning approach by Yeong, Su Yen

    Published 2022
    “…Finally, the model was pickled and loaded into the web application. …”
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  11. 11
    Daily maximum load forecasting of consecutive national holidays using OSELM-based multi-agents system with weighted average strategy

    Daily maximum load forecasting of consecutive national holidays using OSELM-based multi-agents system with weighted average strategy by Yap K.S., Yap H.J.

    Published 2023
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  12. 12
    Development of vehicle detection and counting system for traffic analysis using computer vision

    Development of vehicle detection and counting system for traffic analysis using computer vision by Saw, Kenny Wei Wen

    Published 2024
    “…Initially, the image and video dataset of road traffic is gathered from various online sources and undergoes categorization before loaded into the system for model training. Then two model training process begins, one is for vehicle model detection to learn the feature of a vehicle and the image background, while another training is for binary weather classification for rainy and sunny conditions. …”
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  13. 13
    Electricity Anomaly Point Detection using Unsupervised Technique Based on Electricity Load Prediction Derived from Long Short-Term Memory

    Electricity Anomaly Point Detection using Unsupervised Technique Based on Electricity Load Prediction Derived from Long Short-Term Memory by Salleh N.S.M., Saripuddin M., Suliman A., Jorgensen B.N.

    Published 2023
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  14. 14
    Global Algorithms for Nonlinear Discrete Optimization and Discrete-Valued Optimal Control Problems

    Global Algorithms for Nonlinear Discrete Optimization and Discrete-Valued Optimal Control Problems by Woon, Siew Fang

    Published 2009
    “…We then consider the task of determining near globally optimal solutions of discrete-valued optimal control problems. …”
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  15. 15
    Driver behaviour classification: a research using OBD-II data and machine learning

    Driver behaviour classification: a research using OBD-II data and machine learning by Muhamad Fadzil, Nur Farisya Aqilah, Mohd Fadzir, Hilda, Mansor, Hafizah, Rahardja, Untung

    Published 2024
    “…The relationship between all features and engine speed is analysed to select the optimal features, which include engine speed, vehicle speed, throttle position, and calculated engine load. Then, the proposed model makes use of the K-Means algorithm to create driving behaviour labels whether belong to safe or aggressive - validated by the safety score criteria. …”
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  16. 16
    An Evolutionary Stream Clustering Technique for Outlier Detection

    An Evolutionary Stream Clustering Technique for Outlier Detection by Supardi, N.A., Abdulkadir, S.J., Aziz, N.

    Published 2020
    “…Later, this algorithm will be extended to optimize the model in detecting outlier on data streams. …”
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  17. 17
    Teleworking monitoring system using NILM and K-NN algorithms: a strategy for sustainable smart cities

    Teleworking monitoring system using NILM and K-NN algorithms: a strategy for sustainable smart cities by Yang, Chuan Choong, Noh, Adriana, Ibrahim, Siti Noorjannah, Asnawi, Ani Liza, Mohamed Azmin, Nor Fadhillah

    Published 2024
    “…Together with an event classification method known as K-Nearest Neighbor (k-NN) algorithm, the teleworking event and duration can be identified.The results were presented using classification metrics that consist of confusion matrix andaccuracy score. …”
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  18. 18
    A sequential handwriting recognition model based on a dynamically configurable CRNN

    A sequential handwriting recognition model based on a dynamically configurable CRNN by Al-Saffar, Ahmed, Suryanti, Awang, Al-Saiagh, Wafaa, Al-Khaleefa, Ahmed Salih, Abed, Saad Adnan

    Published 2021
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  19. 19
    Direct Adaptive Predictive Control For Wastewater Treatment Plant

    Direct Adaptive Predictive Control For Wastewater Treatment Plant by Shair, Ezreen Farina, Abu Bakar, Norazhar, Mohd Nor, Arfah Syahida, Mohd Azam, Sazuan Nazrah, Mohd Sobran, Nur Maisarah, Zainal Abidin, Amar Faiz

    Published 2012
    “…This N4SID plays the role of the software sensor for on-line estimation of prediction matrices and control matrices of the bioprocess, joint together with model predictive control (MPC) in order to obtain the optimal control sequence. …”
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  20. 20
    Ganoderma boninense classification based on near-infrared spectral data using machine learning techniques

    Ganoderma boninense classification based on near-infrared spectral data using machine learning techniques by Mas Ira Syafila, Mohd Hilmi Tan, Mohd Faizal, Jamlos, Ahmad Fairuz, Omar, Kamarulzaman, Kamarudin, Mohd Aminudin, Jamlos

    Published 2022
    “…High accuracy shows the capability of the classification model to correctly predict the G. boninense detection while high F1-score indicates that the classification is able to validate the detection of G. boninense correctly with low misclassification rate. …”
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